The efficacy of interventions that target automatic inferences
Understanding harmful or maladaptive behaviour such as addictive, prejudiced, or environmental unfriendly behaviour is a key challenge for psychological science. A highly influential idea is that harmful behaviour is the outcome of implicit, associative processes rather than explicit, belief-based processes that drive more controlled or thoughtful behaviour. For instance, much prejudice, addiction, and behaviour modification research has built on the assumption that the automatic activation of associations between mental representations underlies automatic stimulus evaluation that translates into maladaptive behaviour.
Recent findings challenge this dual-process idea and suggest that belief-based, inferential, processes underlie not only thoughtful and adaptive behaviour, but also more automatic and maladaptive behaviour. Yet, single-process inferential accounts are often criticized for being weakly specified, unfalsifiable, and for showing applied value only in specific contexts with weak generalizability.
Building on the novel idea that automatic inferences determine human behaviour, this project takes up the challenge of elucidating the processes underlying harmful and maladaptive behaviour. Most importantly, it will test the applied value of an inferential theory of behavior and will address the question of how effective are interventions that target automatic inferences to reduce maladaptive behaviour. We will focus on inference training and inference nudging interventions.
To answer these questions, we will draw on recent insights in cognitive (neuro-) science, and social, clinical, and motivation psychology, bridging the gap between these disciplines. The aim is to further develop an integrative theory of the automatic inferential processes that underlie maladaptive behaviour and test the applied value of this theory for changing societally relevant behaviour for which effective interventions are urgently needed.